Specific characteristics of this model are shown in this table.
| Item | Details |
|---|---|
| Disease | Cholera |
| ModelingGroup | JHU-Lee |
| YearRange | 2000-2100 |
| AgeRange | 0-100 |
| CountryList | AFG - AGO - BDI - BEN - BFA - BGD - CAF - CIV - CMR - COD - COG - DZA - ETH - GHA - GIN - GNB - HTI - IND - IRN - IRQ - KEN - LBR - MDG - MLI - MOZ - MRT - MWI - NAM - NER - NGA - NPL - PAK - PHL - RWA - SEN - SLE - SOM - SSD - TCD - TGO - THA - TZA - UGA - YEM - ZAF - ZMB - ZWE |
| SimulatedOutcomes | cohort_size - cases - deaths - dalys - yll |
The trends of the specific coverage sets per campaign scenario can be observed in this figure. For the ocv1-ocv2-default scenario, the coverage reported here is the adjusted coverage from montagu, which is modified to consider the fact that there is no correlation between rounds ‘OCV1’ and ‘OCV2’.
Modelled number of vaccinated people and the number of vaccinated people per country/year as calculated using the coverage tables from montagu. Note that there could be cases where the modelled number of vaccinated people can me different from the number of vaccinated people calculated using the montagu data.
## Warning: Removed 4 rows containing missing values (`geom_bar()`).
This only applies to the ocv1-ocv2 scenario and uses the unadjusted montagu coverage to calculate the number of people vaccinated at rounds ‘OCV1’ and ‘OCV2’ and the adjusted montagu coverage to calculate the number of people who received at least one dose of the vaccine. In the table below, we show only cases where the number of people vaccinated with at least one dose is higher than the number of people who reveived either round ‘OCV1’ or round ‘OCV2’
## Joining with `by = join_by(country_code, year)`
| country_code | year | OCV1 | OCV2 | vp_at_least_one_dose |
|---|---|---|---|---|
| BGD | 2028 | 66510937 | 54773713 | 18702819 |
| BGD | 2034 | 69772263 | 57459510 | 19619902 |
| BGD | 2040 | 72299706 | 59540934 | 20330617 |
| CMR | 2028 | 10481268 | 8631632 | 6063503 |
| CMR | 2034 | 12068206 | 9938523 | 6981558 |
| CMR | 2040 | 13746073 | 11320295 | 7952214 |
| GHA | 2028 | 12529545 | 10318449 | 6273129 |
| GHA | 2034 | 13900462 | 11447439 | 6959502 |
| GHA | 2040 | 15297706 | 12598111 | 7659057 |
| GNB | 2028 | 883961 | 727968 | 224804 |
| GNB | 2034 | 994385 | 818906 | 252886 |
| GNB | 2040 | 1106027 | 910846 | 281279 |
| MDG | 2025 | 26256159 | 21622719 | 24711677 |
| MDG | 2031 | 30102928 | 24790646 | 28332166 |
| MDG | 2037 | 34093390 | 28076909 | 32087897 |
| RWA | 2025 | 12182419 | 10032580 | 11465805 |
| RWA | 2031 | 13840888 | 11398379 | 13026717 |
| RWA | 2037 | 15530964 | 12790206 | 14617379 |
| SEN | 2025 | 15406375 | 12687603 | 14500122 |
| SEN | 2031 | 17869234 | 14715840 | 16818105 |
| SEN | 2037 | 20561411 | 16932927 | 19351920 |
| SOM | 2031 | 8552975 | 7043627 | 2076708 |
| SOM | 2037 | 10081598 | 8302493 | 2447865 |
| TCD | 2028 | 6173631 | 5084166 | 4951200 |
| TCD | 2034 | 7310022 | 6020018 | 5862576 |
| TCD | 2040 | 8540420 | 7033287 | 6849348 |
| ZAF | 2025 | 51486116 | 42400331 | 48457517 |
| ZAF | 2031 | 54525478 | 44903335 | 51318098 |
| ZAF | 2037 | 57151237 | 47065725 | 53789401 |
Age ranges of the different coverage sets include either standard age ranges (as it is the case of Measles) but sometimes it differs by year and country so that several combinations can be possible (See table below).
| coverage_set_name | age_from | age_to | freq |
|---|---|---|---|
| cholera-ocv1-default | 1 | 100 | 309 |
| coverage_set_name | age_from | age_to | freq |
|---|---|---|---|
| cholera-ocv1-ocv2-default | 1 | 100 | 618 |
The estimates of vaccinated people (VP) are obtained by multiplying coverage from each coverage set in Montagu (after adjustment for the ocv1-ocv2-default scenario) and the target population. The following graphs show the number of Vaccinated People (VP) at a global level by scenario.
Expected number of rows.
| scenario_description | outcome_code | number_of_non_na_rows |
|---|---|---|
| Campaign, ocv1-Default | cohort_size | 479447 |
| Campaign, ocv1-Default | cases | 479447 |
| Campaign, ocv1-Default | deaths | 479447 |
| Campaign, ocv1-Default | dalys | 479447 |
| Campaign, ocv1-Default | yll | 479447 |
| No vaccination | cohort_size | 479447 |
| No vaccination | cases | 479447 |
| No vaccination | deaths | 479447 |
| No vaccination | dalys | 479447 |
| No vaccination | yll | 479447 |
| scenario_description | outcome_code | number_of_non_na_rows |
|---|---|---|
| Campaign, ocv2-Default | cohort_size | 479447 |
| Campaign, ocv2-Default | cases | 479447 |
| Campaign, ocv2-Default | deaths | 479447 |
| Campaign, ocv2-Default | dalys | 479447 |
| Campaign, ocv2-Default | yll | 479447 |
| No vaccination | cohort_size | 479447 |
| No vaccination | cases | 479447 |
| No vaccination | deaths | 479447 |
| No vaccination | dalys | 479447 |
| No vaccination | yll | 479447 |
This figure shows the shape of the upload by scenarios and outcomes (whether there are missing values, 1 means no missing value).
This figure shows the pattern of positive values (number of positive values across all simulated countries).
This figure shows the comparison of cohort size against interpolated population in all countries.
This figure shows the comparison of cohort size against interpolated population in the simulated countries.
This figure shows the aggregated (for all countries) age distribution patterns by outcome.
This figure shows the global (simulated countries) burden values by decades 2000-2030.
This figure shows the global (simulated countries) burden disease values 2000-2100.
This figure shows every single simulated countries’ estimated case values and differences 2000-2100.
This figure shows every single simulated countries’ estimated deaths values and differences 2000-2100.